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ISBN 10: 1611976073 ISBN 13: 9781611976076
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Publicado por SIAM - Society for Industrial and Applied Mathematics, 2020
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Publicado por SIAM - Society for Industrial and Applied Mathematics, 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
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ISBN 10: 1611976073 ISBN 13: 9781611976076
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Añadir al carritoPaperback. Condición: new. Paperback. Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks.This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics. Interpolatory methods are among the most widely used model reduction techniques. This book is the first comprehensive analysis of this approach available in a single, extensive resource. It covers both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Publicado por Society for Industrial & Applied Mathematics,U.S., 2020
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Publicado por Society for Industrial and Applied Mathematics, 2009
ISBN 10: 0898716586 ISBN 13: 9780898716580
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Añadir al carritoCondición: Fine. 510 pp., paperback, previous owner's name to inside front cover, else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Photos available upon request.
Publicado por Society for Industrial and Applied Mathematics,U.S., US, 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
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Añadir al carritoPaperback. Condición: New. Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks.This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics.
Publicado por Society for Industrial and Applied Mathematics, 2009
ISBN 10: 0898716586 ISBN 13: 9780898716580
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Añadir al carritoCondición: New. 2009. 1st Edition. Paperback. Series: Advances in Design and Control. 510 pages. Approximation of Large-Scale Dynamical Systems provides a comprehensive picture of model reduction. Cateogry: (P) Professional & Vocational. BIC Classification: PBWR. Dimension: 253 x 172 x 26. Weight: 894. . . . . .
Publicado por Society for Industrial and Applied Mathematics, 2009
ISBN 10: 0898716586 ISBN 13: 9780898716580
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Publicado por Society for Industrial & Applied Mathematics,U.S., 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
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Publicado por Society for Industrial & Applied Mathematics,U.S., 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
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Añadir al carritoCondición: New. Interpolatory methods are among the most widely used model reduction techniques. This book is the first comprehensive analysis of this approach available in a single, extensive resource. It covers both classical projection frameworks for model reduction and.
Publicado por Society for Industrial & Applied Mathematics,U.S., New York, 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
Idioma: Inglés
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Añadir al carritoPaperback. Condición: new. Paperback. Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks.This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics. Interpolatory methods are among the most widely used model reduction techniques. This book is the first comprehensive analysis of this approach available in a single, extensive resource. It covers both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Publicado por Society for Industrial & Applied Mathematics,U.S., 2009
ISBN 10: 0898716586 ISBN 13: 9780898716580
Idioma: Inglés
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Publicado por Society for Industrial and Applied Mathematics, 2009
ISBN 10: 0898716586 ISBN 13: 9780898716580
Idioma: Inglés
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Añadir al carritoCondición: New. 2009. 1st Edition. Paperback. Series: Advances in Design and Control. 510 pages. Approximation of Large-Scale Dynamical Systems provides a comprehensive picture of model reduction. Cateogry: (P) Professional & Vocational. BIC Classification: PBWR. Dimension: 253 x 172 x 26. Weight: 894. . . . . . Books ship from the US and Ireland.
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Añadir al carritoPaperback. Condición: Brand New. reprint edition. 605 pages. 8.75x6.00x1.25 inches. In Stock.
Publicado por Springer Berlin Heidelberg, 2014
ISBN 10: 3662085488 ISBN 13: 9783662085486
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Over the past three decades R.E. Kalman has been one of the most influential personalities in system and control theory. His ideas have been instrumental in a variety of areas. This is a Festschrift honoring his 60th birthday. It contains contributions from leading researchers in the field giving an account of the profound influence of his ideas in a number of areas of active research in system and control theory. For example, since their introduction by Kalman in the early 60's, the concepts of controllability and observability of dynamical systems with inputs, have been the corner stone of the great majority of investigations in the field.
Publicado por Society For Industrial & Applied Mathematics,U.S. Feb 2020, 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks.This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics.
Publicado por Society for Industrial & Applied Mathematics,U.S., 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: Neu. Interpolatory Methods for Model Reduction | Athanasios C. Antoulas | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | Society for Industrial & Applied Mathematics,U.S. | EAN 9781611976076 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Publicado por Society for Industrial and Applied Mathematics,U.S., US, 2020
ISBN 10: 1611976073 ISBN 13: 9781611976076
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoPaperback. Condición: New. Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks.This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics.